GPU-accelerated computing drives current scientific research. Writing fast numeric algorithms for GPUs offers high application performance by offloading compute-intensive portions of the code to the GPU. The course will cover basic aspects of GPU architectures and programming. Focus is on the usage of the directive-based OpenACC programming model which allows for portable application development. Examples of increasing complexity will be used to demonstrate optimization and tuning of scientific applications.

Topics covered will include:

Introduction to GPU/Parallel computing

Programming model OpenACC

Interoperability of OpenACC with GPU libraries (like cuBLAS and cuFFT) and CUDA

Multi-GPU Programming with MPI and OpenACC

Tools for debugging and profiling

Performance optimization

The course consists of lectures and interactive hands-on sessions in C or Fortran (the attendee’s choice).

Prerequisites:

Some knowledge about Linux, e.g. make, command line editor, Linux shell (see for instance this overview), experience in C

Please register with Andreas Herten (a.herten@fz-juelich.de) until 12 October 2020.
If you do not belong to the staff of Forschungszentrum Jülich, we need these data for registration:
Given name, name, birthday, nationality, complete home address, email address

JSC Events - Measures Regarding the Coronavirus Pandemic

Due to the preventive measures at Forschungszentrum Jülich regarding the spread of the Coronavirus, JSC courses were cancelled or postponed. For the time being and with the rapidly changing situation in mind, JSC cannot foresee whether courses and events in the next months can take place as scheduled as face-2-face events. Seminars will preferably be streamed as video conferences, courses might be postponed or partly given as webinars. We still take registrations for the upcoming courses. All participants who registered for courses so far will be notified by e-mail after the regular registration deadline whether and how the courses will be held.